?

如圖左邊5層網絡很顯然可以看作是右邊的3層網絡兩個組合而成的，所以左邊的5層網絡的迭代次數和右邊的3層網絡的迭代次數有沒有什么關系？

5層	3層
2*10*2*10*2	2*10*2
3*10*3*10*3	3*10*3
4*10*4*10*4	4*10*4

本文通過改變節點數制作了3對網絡，比較兩種網絡迭代次數之間的關系。

制作一個5層的網絡

這個網絡的結構是3*10*3*10*3，輸入3個值，輸出3個值。在這個實驗中讓 輸入固定都是0.1，輸出固定都是（1，0，0）。將這個網絡簡寫成

（0.1）-3*10*3*10*3-(3*k)，k∈{0,1}

這個網絡的收斂標準是

if (Math.abs(f4[0]-y[0])< δ? &&? Math.abs(f4[1]-y[1])< δ? &&? Math.abs(f4[2]-y[2])< δ? )

具體進樣順序	?	?	?
δ=0.5	迭代次數	?	?
0.1	1	判斷是否達到收斂
梯度下降	?	?	?
0.1	2	判斷是否達到收斂
梯度下降	?	?	?
……	?	?	?
每當網路達到收斂標準記錄迭代次數
將這一過程重復199次		?	?
δ=0.4	?	?	?
……	?	?	?
δ=1e-7	?	?	?

因為對應每個收斂標準δ都有一個特征的迭代次數n與之對應因此可以用迭代次數曲線n(δ)來評價網絡性能。

本文嘗試了δ從1e-7到0.5的共35個值。收斂時記錄迭代次數n-3*10*3*10*3.

將這個過程重復199次取平均值為n。共收斂了35*199次。

本文還制作了兩外兩個網絡

（0.1）-2*10*2*10*2-(2*k)，k∈{0,1}

（0.1）-4*10*4*10*4-(4*k)，k∈{0,1}

用同樣的辦法可以得到n-2*10*2*10*2和n-4*10*4*10*4.

得到表格

?	2*10*2*10*2	3*10*3*10*3	4*10*4*10*4	?	?
δ	迭代次數n	迭代次數n	迭代次數n	d2/d4	d3/d4
0.5	1.934673367	1.959798995	3	0.644891	0.653266
0.4	5.371859296	5.341708543	7	0.767408	0.763101
0.3	10.27135678	10.18090452	11	0.93376	0.925537
0.2	18.66331658	18.52763819	20	0.933166	0.926382
0.1	40.10050251	38.36683417	39	1.028218	0.983765
0.01	325.6130653	268.5025126	237	1.373895	1.132922
0.001	2280.115578	1684.38191	1406	1.621704	1.197996
1.00E-04	15835.47739	12056.8191	10609	1.492646	1.136471
9.00E-05	17342.0603	13253.43719	11717	1.480077	1.131129
8.00E-05	19208.1206	14739.47739	13077	1.468848	1.12713
7.00E-05	21562.95477	16633.47236	14844	1.452638	1.120552
6.00E-05	24676.82412	19138.08543	17197	1.434949	1.112873
5.00E-05	28974.85427	22613.09045	20480	1.414788	1.104155
4.00E-05	35289.97487	27783.49749	25306	1.39453	1.097902
3.00E-05	45565.71357	36295.21106	33318	1.367601	1.089357
2.00E-05	65556.1005	53122.43719	49468	1.325222	1.073875
1.00E-05	123256.9196	102725.196	97258	1.267319	1.056213
9.00E-06	135849.9447	113718.9146	108216	1.255359	1.050851
8.00E-06	151453.6382	127307.3518	121518	1.246347	1.047642
7.00E-06	171409.3065	144868.4121	139247	1.230973	1.04037
6.00E-06	197814.8894	168071.0653	161784	1.22271	1.038861
5.00E-06	234464.0503	200668.6884	193666	1.210662	1.036159
4.00E-06	288965.3467	249317.9447	241691	1.195598	1.031557
3.00E-06	378816.8543	330180.2663	322513	1.174579	1.023774
2.00E-06	556550.6985	491437.4623	482398	1.153717	1.018739
1.00E-06	1080983.186	974155.5427	964074	1.121266	1.010457
9.00E-07	1208133.623	1080634.106	1072751	1.126201	1.007348
8.00E-07	1353904.367	1215191.643	1206559	1.12212	1.007155
7.00E-07	1539773.07	1387027.477	1381749	1.114365	1.00382
6.00E-07	1786506.508	1616167.709	1606431	1.112097	1.006061
5.00E-07	2133555.362	1937818.854	1931582	1.104564	1.003229
4.00E-07	2646545.613	2418741.794	2414921	1.095914	1.001582
3.00E-07	3500985.513	3222108.256	3226161	1.085186	0.998744
2.00E-07	5199169.422	4828569.704	4839273	1.07437	0.997788
1.00E-07	1.03E+07	9653872.432	9700878	1.057468	0.995155

當δ∈[4e-7,0.01]

d-2*10*2*10*2> d-3*10*3*10*3> d-4*10*4*10*4

但是當δ<4e-7時d-3*10*3*10*3< d-4*10*4*10*4

再制作一個三層的網絡

比照5層網絡將這個網絡寫成

（0.1）-3*10*3-(3*k)，k∈{0,1}

用同樣的辦法可以得到迭代次數n-3*10*3

同樣制作了另外兩個3層的網絡

（0.1）-2*10*2-(2*k)，k∈{0,1}

（0.1）-4*10*4-(4*k)，k∈{0,1}

可以得到迭代次數n-2*10*2和n-4*10*4

得到表格

?	2*10*2	3*10*3	4*10*4	?	?
δ	迭代次數n	迭代次數n	迭代次數n	d2/d4	d3/d4
0.5	1.834170854	2.150753769	4	0.458543	0.537688
0.4	5.467336683	5.668341709	7	0.781048	0.809763
0.3	10.3718593	10.52763819	12	0.864322	0.877303
0.2	18.98492462	19.09547739	21	0.904044	0.909308
0.1	41.81407035	41.92964824	43	0.97242	0.975108
0.01	405.9145729	400.9246231	397	1.022455	1.009886
0.001	3909.160804	3785.150754	3660	1.068077	1.034194
1.00E-04	38025.66332	35887.74372	33662	1.129632	1.06612
9.00E-05	42192.34171	39777.31156	37338	1.130011	1.065331
8.00E-05	47395.70352	44621.80905	41802	1.133814	1.067456
7.00E-05	54052.65327	50836.96482	47443	1.139318	1.071538
6.00E-05	62950.38191	59079.18593	55259	1.139188	1.069132
5.00E-05	75340.25628	70575.01005	65584	1.14876	1.076101
4.00E-05	93917.48744	87725.11558	81242	1.156021	1.0798
3.00E-05	124764.8342	116155.4975	107253	1.163276	1.083005
2.00E-05	186176.5779	172366.9598	158480	1.174764	1.087626
1.00E-05	368710.8643	338333.7889	308464	1.195312	1.096834
9.00E-06	408984.0804	375023.1005	341247	1.198499	1.098978
8.00E-06	459388.5276	420561.8643	382394	1.201349	1.099813
7.00E-06	524038.9497	478899.1457	435268	1.203945	1.10024
6.00E-06	609813.0704	556314.598	504206	1.209452	1.103348
5.00E-06	729919.3065	664199.0553	600920	1.21467	1.105304
4.00E-06	909130.6181	825530.8241	744853	1.22055	1.108314
3.00E-06	1207124.558	1091742.894	980381	1.231281	1.11359
2.00E-06	1799195.739	1619069.065	1449669	1.241108	1.116854
1.00E-06	3559300.412	3175825.116	2818734	1.26273	1.126685
9.00E-07	3947484.774	3517441.141	3123123	1.263954	1.126258
8.00E-07	4433661.618	3943425.156	3493458	1.269133	1.128803
7.00E-07	5056311.834	4490016.492	3972648	1.272781	1.130233
6.00E-07	5882920.477	5216202.241	4605197	1.277453	1.132677
5.00E-07	7040336.97	6225307.176	5492530	1.281802	1.133413
4.00E-07	8766715.804	7731842.281	6800941	1.289045	1.136878
3.00E-07	1.16E+07	1.02E+07	8973350	1.296219	1.139355
2.00E-07	1.73E+07	1.52E+07	1.32E+07	1.308507	1.144752
1.00E-07	3.42E+07	2.97E+07	2.58E+07	1.327545	1.151904

?

這個結論是很清晰的

d-2*10*2>d-3*10*3>d-4*10*4.

比較兩個網絡

（0.1）-3*10*3*10*3-(3*k)，k∈{0,1}

（0.1）-3*10*3-(3*k)，k∈{0,1}

很顯然這個5層的網絡可以理解成是兩個3層的網絡組合成的，所以迭代次數n-3*10*3*10*3和n-3*10*3之間有什么關系？

δ	d-2*10*2/d-2*10*2*10*2	d-3*10*3/d-3*10*3*10*3	d-4*10*4/d-4*10*4*10*4
0.5	0.948051948	1.097435897	1.333333333
0.4	1.01777362	1.061147695	1
0.3	1.009784736	1.034057256	1.090909091
0.2	1.017232095	1.030648223	1.05
0.1	1.04273183	1.092861821	1.102564103
0.01	1.246616356	1.493187603	1.675105485
0.001	1.714457303	2.247204587	2.603129445
1.00E-04	2.401295672	2.976551563	3.172966349
9.00E-05	2.432948622	3.001282686	3.186651873
8.00E-05	2.467482608	3.027367109	3.196604726
7.00E-05	2.506736847	3.056305005	3.196106171
6.00E-05	2.55099204	3.086995622	3.213293016
5.00E-05	2.600194485	3.12098031	3.20234375
4.00E-05	2.661307858	3.157454011	3.210384889
3.00E-05	2.738129712	3.200298169	3.219070773
2.00E-05	2.839958089	3.244711066	3.203687232
1.00E-05	2.991400933	3.293581343	3.171605421
9.00E-06	3.010557577	3.297807598	3.153387669
8.00E-06	3.033195723	3.303515928	3.146809526
7.00E-06	3.057237441	3.30575271	3.125869857
6.00E-06	3.082746056	3.309996262	3.1165381
5.00E-06	3.113139544	3.309928721	3.102867824
4.00E-06	3.146157933	3.311156865	3.081840035
3.00E-06	3.186565075	3.306505584	3.03981855
2.00E-06	3.232761622	3.294557679	3.005130618
1.00E-06	3.292651041	3.260080117	2.923773486
9.00E-07	3.267423982	3.254978834	2.911321453
8.00E-07	3.274722888	3.245105558	2.895389285
7.00E-07	3.283803264	3.237150356	2.875086575
6.00E-07	3.292974558	3.22751297	2.866725679
5.00E-07	3.299814524	3.212533082	2.843539648
4.00E-07	3.312512643	3.196638145	2.816216762
3.00E-07	3.322328032	3.173025172	2.781432793
2.00E-07	3.332789289	3.139484946	2.736437271
1.00E-07	3.33782706	3.077567328	2.658776041

1.00E-07	d-2*10*2	>	d-2*10*2*10*2	3.33
1.00E-07	d-3*10*3	>	d-3*10*3*10*3	3.07
1.00E-07	d-4*10*4	>	d-4*10*4*10*4	2.65

一個大致的結論是在絕大多數區間上三層網路的迭代次數都要大于對應5層網絡的迭代次數。比例并不固定但大于2倍。

學習率 0.1

權重初始化方式

Random rand1 =new Random();

int ti1=rand1.nextInt(98)+1;

int xx=1;

if(ti1%2==0)

{ xx=-1;}

tw[a][b]=xx*((double)ti1/1000); ?

?

d0.1-2-10-2-10-2?? ??? ??? ??? ??? ??? ?
??? ??? ??? ??? ??? ??? ??? ?
f2[0]?? ?f2[1]?? ?迭代次數n?? ?平均準確率p-ave?? ?δ?? ?耗時ms/次?? ?耗時ms/199次?? ?耗時 min/199
0.528641?? ?0.470845?? ?1.934673?? ?0?? ?0.5?? ?0.472362?? ?94?? ?0.001567
0.620223?? ?0.38049?? ?5.371859?? ?0?? ?0.4?? ?0.155779?? ?31?? ?0.000517
0.713105?? ?0.28614?? ?10.27136?? ?0?? ?0.3?? ?0.236181?? ?47?? ?0.000783
0.806761?? ?0.192324?? ?18.66332?? ?0?? ?0.2?? ?0.155779?? ?47?? ?0.000783
0.902126?? ?0.098016?? ?40.1005?? ?0?? ?0.1?? ?0.316583?? ?63?? ?0.00105
0.990028?? ?0.009965?? ?325.6131?? ?0?? ?0.01?? ?2.437186?? ?485?? ?0.008083
0.999001?? ?9.99E-04?? ?2280.116?? ?0?? ?0.001?? ?14.35678?? ?2857?? ?0.047617
0.9999?? ?1.00E-04?? ?15835.48?? ?0?? ?1.00E-04?? ?91.31658?? ?18172?? ?0.302867
0.99991?? ?9.00E-05?? ?17342.06?? ?0?? ?9.00E-05?? ?92.51256?? ?18411?? ?0.30685
0.99992?? ?8.00E-05?? ?19208.12?? ?0?? ?8.00E-05?? ?102.7085?? ?20439?? ?0.34065
0.99993?? ?7.00E-05?? ?21562.95?? ?0?? ?7.00E-05?? ?117.6583?? ?23429?? ?0.390483
0.99994?? ?6.00E-05?? ?24676.82?? ?0?? ?6.00E-05?? ?132.7186?? ?26411?? ?0.440183
0.99995?? ?5.00E-05?? ?28974.85?? ?0?? ?5.00E-05?? ?155.8442?? ?31013?? ?0.516883
0.99996?? ?4.00E-05?? ?35289.97?? ?0?? ?4.00E-05?? ?190.0251?? ?37815?? ?0.63025
0.99997?? ?3.00E-05?? ?45565.71?? ?0?? ?3.00E-05?? ?244.0704?? ?48570?? ?0.8095
0.99998?? ?2.00E-05?? ?65556.1?? ?0?? ?2.00E-05?? ?353.6633?? ?70379?? ?1.172983
0.99999?? ?1.00E-05?? ?123256.9?? ?0?? ?1.00E-05?? ?662.1508?? ?131768?? ?2.196133
0.999991?? ?9.00E-06?? ?135849.9?? ?0?? ?9.00E-06?? ?729.8794?? ?145246?? ?2.420767
0.999992?? ?8.00E-06?? ?151453.6?? ?0?? ?8.00E-06?? ?811.5477?? ?161498?? ?2.691633
0.999993?? ?7.00E-06?? ?171409.3?? ?0?? ?7.00E-06?? ?924.8392?? ?184043?? ?3.067383
0.999994?? ?6.00E-06?? ?197814.9?? ?0?? ?6.00E-06?? ?1064.402?? ?211816?? ?3.530267
0.999995?? ?5.00E-06?? ?234464.1?? ?0?? ?5.00E-06?? ?1265.804?? ?251895?? ?4.19825
0.999996?? ?4.00E-06?? ?288965.3?? ?0?? ?4.00E-06?? ?1556.377?? ?309720?? ?5.162
0.999997?? ?3.00E-06?? ?378816.9?? ?0?? ?3.00E-06?? ?2045.628?? ?407080?? ?6.784667
0.999998?? ?2.00E-06?? ?556550.7?? ?0?? ?2.00E-06?? ?2993.387?? ?595699?? ?9.928317
0.999999?? ?1.00E-06?? ?1080983?? ?0?? ?1.00E-06?? ?5829.889?? ?1160148?? ?19.3358
0.999999?? ?9.00E-07?? ?1208134?? ?0?? ?9.00E-07?? ?6812.869?? ?1355770?? ?22.59617
0.999999?? ?8.00E-07?? ?1353904?? ?0?? ?8.00E-07?? ?7593.246?? ?1511063?? ?25.18438
0.999999?? ?7.00E-07?? ?1539773?? ?0?? ?7.00E-07?? ?8703.136?? ?1731927?? ?28.86545
0.999999?? ?6.00E-07?? ?1786507?? ?0?? ?6.00E-07?? ?10142.74?? ?2018416?? ?33.64027
1?? ?5.00E-07?? ?2133555?? ?0?? ?5.00E-07?? ?10983.01?? ?2185627?? ?36.42712
1?? ?4.00E-07?? ?2646546?? ?0?? ?4.00E-07?? ?14397.07?? ?2865023?? ?47.75038
1?? ?3.00E-07?? ?3500986?? ?0?? ?3.00E-07?? ?18074.47?? ?3596836?? ?59.94727
1?? ?2.00E-07?? ?5199169?? ?0?? ?2.00E-07?? ?28020.73?? ?5576127?? ?92.93545
1?? ?1.00E-07?? ?1.03E+07?? ?0?? ?1.00E-07?? ?55535.69?? ?11051602?? ?184.1934
?? ??? ??? ??? ??? ??? ??? ?
?? ??? ??? ??? ??? ??? ??? ?595.8261
?? ??? ??? ??? ??? ??? ??? ??
? ? ??
?? ??? ??? ??? ??? ??? ??? ?
d0.1*2*10*2?? ??? ??? ??? ??? ??? ?
??? ??? ??? ??? ??? ??? ??? ?
f2[0]?? ?f2[1]?? ?迭代次數n?? ?平均準確率p-ave?? ?δ?? ?耗時ms/次?? ?耗時ms/199次?? ?耗時 min/199
0.525464?? ?0.470535?? ?1.834171?? ?0?? ?0.5?? ?0.472362?? ?94?? ?0.001567
0.621887?? ?0.377717?? ?5.467337?? ?0?? ?0.4?? ?0.311558?? ?62?? ?0.001033
0.713341?? ?0.285849?? ?10.37186?? ?0?? ?0.3?? ?0.236181?? ?47?? ?0.000783
0.806947?? ?0.193202?? ?18.98492?? ?0?? ?0.2?? ?0.236181?? ?47?? ?0.000783
0.901937?? ?0.098125?? ?41.81407?? ?0?? ?0.1?? ?0.155779?? ?47?? ?0.000783
0.99002?? ?0.009976?? ?405.9146?? ?0?? ?0.01?? ?1.648241?? ?328?? ?0.005467
0.999?? ?1.00E-03?? ?3909.161?? ?0?? ?0.001?? ?12.82412?? ?2552?? ?0.042533
0.9999?? ?1.00E-04?? ?38025.66?? ?0?? ?1.00E-04?? ?102.9799?? ?20493?? ?0.34155
0.99991?? ?9.00E-05?? ?42192.34?? ?0?? ?9.00E-05?? ?113.4623?? ?22579?? ?0.376317
0.99992?? ?8.00E-05?? ?47395.7?? ?0?? ?8.00E-05?? ?126.7688?? ?25227?? ?0.42045
0.99993?? ?7.00E-05?? ?54052.65?? ?0?? ?7.00E-05?? ?144.0653?? ?28669?? ?0.477817
0.99994?? ?6.00E-05?? ?62950.38?? ?0?? ?6.00E-05?? ?167.3769?? ?33308?? ?0.555133
0.99995?? ?5.00E-05?? ?75340.26?? ?0?? ?5.00E-05?? ?200.1508?? ?39830?? ?0.663833
0.99996?? ?4.00E-05?? ?93917.49?? ?0?? ?4.00E-05?? ?250.7136?? ?49892?? ?0.831533
0.99997?? ?3.00E-05?? ?124764.8?? ?0?? ?3.00E-05?? ?333.8342?? ?66433?? ?1.107217
0.99998?? ?2.00E-05?? ?186176.6?? ?0?? ?2.00E-05?? ?494.1055?? ?98343?? ?1.63905
0.99999?? ?1.00E-05?? ?368710.9?? ?0?? ?1.00E-05?? ?981.5628?? ?195331?? ?3.255517
0.999991?? ?9.00E-06?? ?408984.1?? ?0?? ?9.00E-06?? ?1096.543?? ?218214?? ?3.6369
0.999992?? ?8.00E-06?? ?459388.5?? ?0?? ?8.00E-06?? ?1233.422?? ?245451?? ?4.09085
0.999993?? ?7.00E-06?? ?524038.9?? ?0?? ?7.00E-06?? ?1400.101?? ?278620?? ?4.643667
0.999994?? ?6.00E-06?? ?609813.1?? ?0?? ?6.00E-06?? ?1633.131?? ?324993?? ?5.41655
0.999995?? ?5.00E-06?? ?729919.3?? ?0?? ?5.00E-06?? ?1953.291?? ?388705?? ?6.478417
0.999996?? ?4.00E-06?? ?909130.6?? ?0?? ?4.00E-06?? ?2433.729?? ?484312?? ?8.071867
0.999997?? ?3.00E-06?? ?1207125?? ?0?? ?3.00E-06?? ?3293.899?? ?655489?? ?10.92482
0.999998?? ?2.00E-06?? ?1799196?? ?0?? ?2.00E-06?? ?4926.965?? ?980469?? ?16.34115
0.999999?? ?1.00E-06?? ?3559300?? ?0?? ?1.00E-06?? ?10112.95?? ?2012481?? ?33.54135
0.999999?? ?9.00E-07?? ?3947485?? ?0?? ?9.00E-07?? ?11262.18?? ?2241184?? ?37.35307
0.999999?? ?8.00E-07?? ?4433662?? ?0?? ?8.00E-07?? ?11642.25?? ?2316810?? ?38.6135
0.999999?? ?7.00E-07?? ?5056312?? ?0?? ?7.00E-07?? ?13749.6?? ?2736171?? ?45.60285
0.999999?? ?6.00E-07?? ?5882920?? ?0?? ?6.00E-07?? ?15936.78?? ?3171436?? ?52.85727
1?? ?5.00E-07?? ?7040337?? ?0?? ?5.00E-07?? ?18808.06?? ?3742809?? ?62.38015
1?? ?4.00E-07?? ?8766716?? ?0?? ?4.00E-07?? ?23278.54?? ?4632436?? ?77.20727
1?? ?3.00E-07?? ?1.16E+07?? ?0?? ?3.00E-07?? ?32613?? ?6489996?? ?108.1666
1?? ?2.00E-07?? ?1.73E+07?? ?0?? ?2.00E-07?? ?47493.48?? ?9451223?? ?157.5204
1?? ?1.00E-07?? ?3.42E+07?? ?0?? ?1.00E-07?? ?95195.08?? ?18943821?? ?315.7304
?? ??? ??? ??? ??? ??? ??? ?
??? ? ?? ? ?? ? ?? ? ?? ? ?? ? ?? ?998.2984

d0.1-3-10-3-10-3?? ??? ??? ??? ??? ??? ??? ?
?? ??? ??? ??? ??? ??? ??? ??? ?
f2[0]?? ?f2[1]?? ?f2[2]?? ?迭代次數n?? ?平均準確率p-ave?? ?δ?? ?耗時ms/次?? ?耗時ms/199次?? ?耗時 min/199
0.527193?? ?0.470014?? ?0.469798?? ?1.959799?? ?0?? ?0.5?? ?0.472362?? ?94?? ?0.001567
0.619754?? ?0.378289?? ?0.380506?? ?5.341709?? ?0?? ?0.4?? ?0.155779?? ?31?? ?0.000517
0.714597?? ?0.286142?? ?0.286613?? ?10.1809?? ?0?? ?0.3?? ?0.236181?? ?47?? ?0.000783
0.808487?? ?0.192633?? ?0.192337?? ?18.52764?? ?0?? ?0.2?? ?0.316583?? ?63?? ?0.00105
0.902196?? ?0.097576?? ?0.097796?? ?38.36683?? ?0?? ?0.1?? ?0.386935?? ?93?? ?0.00155
0.990043?? ?0.009961?? ?0.009955?? ?268.5025?? ?0?? ?0.01?? ?2.276382?? ?453?? ?0.00755
0.999001?? ?9.99E-04?? ?9.99E-04?? ?1684.382?? ?0?? ?0.001?? ?15.29146?? ?3058?? ?0.050967
0.9999?? ?1.00E-04?? ?1.00E-04?? ?12056.82?? ?0?? ?1.00E-04?? ?74.60804?? ?14862?? ?0.2477
0.99991?? ?9.00E-05?? ?9.00E-05?? ?13253.44?? ?0?? ?9.00E-05?? ?78.15075?? ?15552?? ?0.2592
0.99992?? ?8.00E-05?? ?8.00E-05?? ?14739.48?? ?0?? ?8.00E-05?? ?86.64322?? ?17242?? ?0.287367
0.99993?? ?7.00E-05?? ?7.00E-05?? ?16633.47?? ?0?? ?7.00E-05?? ?98.61809?? ?19625?? ?0.327083
0.99994?? ?6.00E-05?? ?6.00E-05?? ?19138.09?? ?0?? ?6.00E-05?? ?113.3417?? ?22555?? ?0.375917
0.99995?? ?5.00E-05?? ?5.00E-05?? ?22613.09?? ?0?? ?5.00E-05?? ?132.2714?? ?26322?? ?0.4387
0.99996?? ?4.00E-05?? ?4.00E-05?? ?27783.5?? ?0?? ?4.00E-05?? ?162.804?? ?32398?? ?0.539967
0.99997?? ?3.00E-05?? ?3.00E-05?? ?36295.21?? ?0?? ?3.00E-05?? ?212.5578?? ?42299?? ?0.704983
0.99998?? ?2.00E-05?? ?2.00E-05?? ?53122.44?? ?0?? ?2.00E-05?? ?311.206?? ?61930?? ?1.032167
0.99999?? ?1.00E-05?? ?1.00E-05?? ?102725.2?? ?0?? ?1.00E-05?? ?604.1658?? ?120229?? ?2.003817
0.999991?? ?9.00E-06?? ?9.00E-06?? ?113718.9?? ?0?? ?9.00E-06?? ?669.7688?? ?133299?? ?2.22165
0.999992?? ?8.00E-06?? ?8.00E-06?? ?127307.4?? ?0?? ?8.00E-06?? ?749.5025?? ?149167?? ?2.486117
0.999993?? ?7.00E-06?? ?7.00E-06?? ?144868.4?? ?0?? ?7.00E-06?? ?854.5678?? ?170059?? ?2.834317
0.999994?? ?6.00E-06?? ?6.00E-06?? ?168071.1?? ?0?? ?6.00E-06?? ?990.9598?? ?197201?? ?3.286683
0.999995?? ?5.00E-06?? ?5.00E-06?? ?200668.7?? ?0?? ?5.00E-06?? ?1182.101?? ?235254?? ?3.9209
0.999996?? ?4.00E-06?? ?4.00E-06?? ?249317.9?? ?0?? ?4.00E-06?? ?1471.251?? ?292795?? ?4.879917
0.999997?? ?3.00E-06?? ?3.00E-06?? ?330180.3?? ?0?? ?3.00E-06?? ?1945.874?? ?387244?? ?6.454067
0.999998?? ?2.00E-06?? ?2.00E-06?? ?491437.5?? ?0?? ?2.00E-06?? ?2906.714?? ?578436?? ?9.6406
0.999999?? ?1.00E-06?? ?1.00E-06?? ?974155.5?? ?0?? ?1.00E-06?? ?5805.045?? ?1155204?? ?19.2534
0.999999?? ?9.00E-07?? ?9.00E-07?? ?1080634?? ?0?? ?9.00E-07?? ?6453.688?? ?1284299?? ?21.40498
0.999999?? ?8.00E-07?? ?8.00E-07?? ?1215192?? ?0?? ?8.00E-07?? ?7235.307?? ?1439826?? ?23.9971
0.999999?? ?7.00E-07?? ?7.00E-07?? ?1387027?? ?0?? ?7.00E-07?? ?8266.302?? ?1644994?? ?27.41657
0.999999?? ?6.00E-07?? ?6.00E-07?? ?1616168?? ?0?? ?6.00E-07?? ?9634.271?? ?1917251?? ?31.95418
1?? ?5.00E-07?? ?5.00E-07?? ?1937819?? ?0?? ?5.00E-07?? ?11562.39?? ?2300915?? ?38.34858
1?? ?4.00E-07?? ?4.00E-07?? ?2418742?? ?0?? ?4.00E-07?? ?14425.52?? ?2870695?? ?47.84492
1?? ?3.00E-07?? ?3.00E-07?? ?3222108?? ?0?? ?3.00E-07?? ?20229.73?? ?4025728?? ?67.09547
1?? ?2.00E-07?? ?2.00E-07?? ?4828570?? ?0?? ?2.00E-07?? ?29352.16?? ?5841084?? ?97.3514
1?? ?1.00E-07?? ?1.00E-07?? ?9653872?? ?0?? ?1.00E-07?? ?58702.82?? ?11681878?? ?194.698
?? ??? ??? ??? ??? ??? ??? ??? ?
?? ??? ??? ??? ??? ??? ??? ??? ?611.3697
?? ??? ??? ??? ??? ??? ??? ??? ?
? ? ? ? ? ?
d0.1-3-10-3?? ??? ??? ??? ??? ??? ??? ?
?? ??? ??? ??? ??? ??? ??? ??? ?
f2[0]?? ?f2[1]?? ?f2[2]?? ?迭代次數n?? ?平均準確率p-ave?? ?δ?? ?耗時ms/次?? ?耗時ms/199次?? ?耗時 min/199
0.53421?? ?0.464075?? ?0.465333?? ?2.150754?? ?0?? ?0.5?? ?0.316583?? ?78?? ?0.0013
0.62713?? ?0.374943?? ?0.373477?? ?5.668342?? ?0?? ?0.4?? ?0.080402?? ?32?? ?0.000533
0.716243?? ?0.282829?? ?0.283456?? ?10.52764?? ?0?? ?0.3?? ?0.155779?? ?31?? ?0.000517
0.807594?? ?0.191996?? ?0.191729?? ?19.09548?? ?0?? ?0.2?? ?0.236181?? ?47?? ?0.000783
0.902494?? ?0.097579?? ?0.097602?? ?41.92965?? ?0?? ?0.1?? ?0.236181?? ?47?? ?0.000783
0.990029?? ?0.009972?? ?0.009973?? ?400.9246?? ?0?? ?0.01?? ?1.884422?? ?375?? ?0.00625
0.999?? ?1.00E-03?? ?1.00E-03?? ?3785.151?? ?0?? ?0.001?? ?12.9799?? ?2599?? ?0.043317
0.9999?? ?1.00E-04?? ?1.00E-04?? ?35887.74?? ?0?? ?1.00E-04?? ?107.5578?? ?21404?? ?0.356733
0.99991?? ?9.00E-05?? ?9.00E-05?? ?39777.31?? ?0?? ?9.00E-05?? ?-216.437?? ?-43071?? ?-0.71785
0.99992?? ?8.00E-05?? ?8.00E-05?? ?44621.81?? ?0?? ?8.00E-05?? ?129.2462?? ?25735?? ?0.428917
0.99993?? ?7.00E-05?? ?7.00E-05?? ?50836.96?? ?0?? ?7.00E-05?? ?149.8442?? ?29819?? ?0.496983
0.99994?? ?6.00E-05?? ?6.00E-05?? ?59079.19?? ?0?? ?6.00E-05?? ?174.3869?? ?34703?? ?0.578383
0.99995?? ?5.00E-05?? ?5.00E-05?? ?70575.01?? ?0?? ?5.00E-05?? ?207.7035?? ?41333?? ?0.688883
0.99996?? ?4.00E-05?? ?4.00E-05?? ?87725.12?? ?0?? ?4.00E-05?? ?262.7387?? ?52316?? ?0.871933
0.99997?? ?3.00E-05?? ?3.00E-05?? ?116155.5?? ?0?? ?3.00E-05?? ?346.3065?? ?68915?? ?1.148583
0.99998?? ?2.00E-05?? ?2.00E-05?? ?172367?? ?0?? ?2.00E-05?? ?508.2111?? ?101134?? ?1.685567
0.99999?? ?1.00E-05?? ?1.00E-05?? ?338333.8?? ?0?? ?1.00E-05?? ?1003.648?? ?199726?? ?3.328767
0.999991?? ?9.00E-06?? ?9.00E-06?? ?375023.1?? ?0?? ?9.00E-06?? ?1112.487?? ?221385?? ?3.68975
0.999992?? ?8.00E-06?? ?8.00E-06?? ?420561.9?? ?0?? ?8.00E-06?? ?1250.854?? ?248920?? ?4.148667
0.999993?? ?7.00E-06?? ?7.00E-06?? ?478899.1?? ?0?? ?7.00E-06?? ?1418.658?? ?282313?? ?4.705217
0.999994?? ?6.00E-06?? ?6.00E-06?? ?556314.6?? ?0?? ?6.00E-06?? ?1648.251?? ?328017?? ?5.46695
0.999995?? ?5.00E-06?? ?5.00E-06?? ?664199.1?? ?0?? ?5.00E-06?? ?1971.07?? ?392275?? ?6.537917
0.999996?? ?4.00E-06?? ?4.00E-06?? ?825530.8?? ?0?? ?4.00E-06?? ?2453.859?? ?488318?? ?8.138633
0.999997?? ?3.00E-06?? ?3.00E-06?? ?1091743?? ?0?? ?3.00E-06?? ?3247.789?? ?646310?? ?10.77183
0.999998?? ?2.00E-06?? ?2.00E-06?? ?1619069?? ?0?? ?2.00E-06?? ?4810.317?? ?957268?? ?15.95447
0.999999?? ?1.00E-06?? ?1.00E-06?? ?3175825?? ?0?? ?1.00E-06?? ?9445.754?? ?1879705?? ?31.32842
0.999999?? ?9.00E-07?? ?9.00E-07?? ?3517441?? ?0?? ?9.00E-07?? ?10347.84?? ?2059237?? ?34.32062
0.999999?? ?8.00E-07?? ?8.00E-07?? ?3943425?? ?0?? ?8.00E-07?? ?11567.7?? ?2301973?? ?38.36622
0.999999?? ?7.00E-07?? ?7.00E-07?? ?4490016?? ?0?? ?7.00E-07?? ?13167.86?? ?2620404?? ?43.6734
0.999999?? ?6.00E-07?? ?6.00E-07?? ?5216202?? ?0?? ?6.00E-07?? ?15299.34?? ?3044568?? ?50.7428
1?? ?5.00E-07?? ?5.00E-07?? ?6225307?? ?0?? ?5.00E-07?? ?18243.98?? ?3630569?? ?60.50948
1?? ?4.00E-07?? ?4.00E-07?? ?7731842?? ?0?? ?4.00E-07?? ?22756.38?? ?4528536?? ?75.4756
1?? ?3.00E-07?? ?3.00E-07?? ?1.02E+07?? ?0?? ?3.00E-07?? ?31021.67?? ?6173330?? ?102.8888
1?? ?2.00E-07?? ?2.00E-07?? ?1.52E+07?? ?0?? ?2.00E-07?? ?45639.92?? ?9082360?? ?151.3727
1?? ?1.00E-07?? ?1.00E-07?? ?2.97E+07?? ?0?? ?1.00E-07?? ?88688.07?? ?17648925?? ?294.1488
?? ??? ??? ??? ??? ??? ??? ??? ?
??? ? ?? ? ?? ? ?? ? ?? ? ?? ? ?? ? ?? ?951.1606

d0.1-4-10-4-10-4?? ??? ??? ??? ??? ??? ??? ??? ?
?? ??? ??? ??? ??? ??? ??? ??? ??? ?
f2[0]?? ?f2[1]?? ?f2[2]?? ?f2[3]?? ?迭代次數n?? ?平均準確率p-ave?? ?δ?? ?耗時ms/次?? ?耗時ms/199次?? ?耗時 min/199
0.525973?? ?0.470305?? ?0.472377?? ?0.472429?? ?3?? ?0?? ?0.5?? ?0.547739?? ?109?? ?0.001817
0.622486?? ?0.377597?? ?0.379318?? ?0.375209?? ?7?? ?0?? ?0.4?? ?0.160804?? ?32?? ?0.000533
0.713703?? ?0.285557?? ?0.286032?? ?0.286273?? ?11?? ?0?? ?0.3?? ?0.311558?? ?62?? ?0.001033
0.807452?? ?0.192672?? ?0.192159?? ?0.192303?? ?20?? ?0?? ?0.2?? ?0.316583?? ?63?? ?0.00105
0.902426?? ?0.097368?? ?0.097147?? ?0.097417?? ?39?? ?0?? ?0.1?? ?0.547739?? ?109?? ?0.001817
0.990052?? ?0.009949?? ?0.009942?? ?0.009945?? ?237?? ?0?? ?0.01?? ?2.201005?? ?438?? ?0.0073
0.999001?? ?9.99E-04?? ?9.99E-04?? ?9.99E-04?? ?1406?? ?0?? ?0.001?? ?10.94472?? ?2210?? ?0.036833
0.9999?? ?9.99E-05?? ?9.99E-05?? ?9.99E-05?? ?10609?? ?0?? ?1.00E-04?? ?72.35176?? ?14415?? ?0.24025
0.99991?? ?9.00E-05?? ?9.00E-05?? ?9.00E-05?? ?11717?? ?0?? ?9.00E-05?? ?77.26131?? ?15385?? ?0.256417
0.99992?? ?8.00E-05?? ?8.00E-05?? ?8.00E-05?? ?13077?? ?0?? ?8.00E-05?? ?84.24121?? ?16768?? ?0.279467
0.99993?? ?7.00E-05?? ?7.00E-05?? ?7.00E-05?? ?14844?? ?0?? ?7.00E-05?? ?102.5628?? ?20433?? ?0.34055
0.99994?? ?6.00E-05?? ?6.00E-05?? ?6.00E-05?? ?17197?? ?0?? ?6.00E-05?? ?116.2764?? ?23143?? ?0.385717
0.99995?? ?5.00E-05?? ?5.00E-05?? ?5.00E-05?? ?20480?? ?0?? ?5.00E-05?? ?136.5075?? ?27185?? ?0.453083
0.99996?? ?4.00E-05?? ?4.00E-05?? ?4.00E-05?? ?25306?? ?0?? ?4.00E-05?? ?169.9799?? ?33831?? ?0.56385
0.99997?? ?3.00E-05?? ?3.00E-05?? ?3.00E-05?? ?33318?? ?0?? ?3.00E-05?? ?226.7538?? ?45131?? ?0.752183
0.99998?? ?2.00E-05?? ?2.00E-05?? ?2.00E-05?? ?49468?? ?0?? ?2.00E-05?? ?334.9296?? ?66656?? ?1.110933
0.99999?? ?1.00E-05?? ?1.00E-05?? ?9.99E-06?? ?97258?? ?0?? ?1.00E-05?? ?661.0955?? ?131561?? ?2.192683
0.999991?? ?9.00E-06?? ?9.00E-06?? ?9.00E-06?? ?108216?? ?0?? ?9.00E-06?? ?731.598?? ?145588?? ?2.426467
0.999992?? ?8.00E-06?? ?8.00E-06?? ?8.00E-06?? ?121518?? ?0?? ?8.00E-06?? ?799.6834?? ?159143?? ?2.652383
0.999993?? ?7.00E-06?? ?7.00E-06?? ?7.00E-06?? ?139247?? ?0?? ?7.00E-06?? ?917.608?? ?182612?? ?3.043533
0.999994?? ?6.00E-06?? ?6.00E-06?? ?6.00E-06?? ?161784?? ?0?? ?6.00E-06?? ?1062.995?? ?211538?? ?3.525633
0.999995?? ?5.00E-06?? ?5.00E-06?? ?5.00E-06?? ?193666?? ?0?? ?5.00E-06?? ?1273.06?? ?253343?? ?4.222383
0.999996?? ?4.00E-06?? ?4.00E-06?? ?4.00E-06?? ?241691?? ?0?? ?4.00E-06?? ?1589.93?? ?316400?? ?5.273333
0.999997?? ?3.00E-06?? ?3.00E-06?? ?3.00E-06?? ?322513?? ?0?? ?3.00E-06?? ?2151.678?? ?428189?? ?7.136483
0.999998?? ?2.00E-06?? ?2.00E-06?? ?2.00E-06?? ?482398?? ?0?? ?2.00E-06?? ?3193.673?? ?635560?? ?10.59267
0.999999?? ?1.00E-06?? ?1.00E-06?? ?1.00E-06?? ?964074?? ?0?? ?1.00E-06?? ?6390.251?? ?1271663?? ?21.19438
0.999999?? ?9.00E-07?? ?9.00E-07?? ?9.00E-07?? ?1072751?? ?0?? ?9.00E-07?? ?7089.07?? ?1410734?? ?23.51223
0.999999?? ?8.00E-07?? ?8.00E-07?? ?8.00E-07?? ?1206559?? ?0?? ?8.00E-07?? ?7998.598?? ?1591723?? ?26.52872
0.999999?? ?7.00E-07?? ?7.00E-07?? ?7.00E-07?? ?1381749?? ?0?? ?7.00E-07?? ?8947.251?? ?1780505?? ?29.67508
0.999999?? ?6.00E-07?? ?6.00E-07?? ?6.00E-07?? ?1606431?? ?0?? ?6.00E-07?? ?10406.81?? ?2070956?? ?34.51593
1?? ?5.00E-07?? ?5.00E-07?? ?5.00E-07?? ?1931582?? ?0?? ?5.00E-07?? ?12522.17?? ?2491915?? ?41.53192
1?? ?4.00E-07?? ?4.00E-07?? ?4.00E-07?? ?2414921?? ?0?? ?4.00E-07?? ?15727.61?? ?3129795?? ?52.16325
1?? ?3.00E-07?? ?3.00E-07?? ?3.00E-07?? ?3226161?? ?0?? ?3.00E-07?? ?20389.41?? ?4057494?? ?67.6249
1?? ?2.00E-07?? ?2.00E-07?? ?2.00E-07?? ?4839273?? ?0?? ?2.00E-07?? ?31133.98?? ?6195679?? ?103.2613
1?? ?1.00E-07?? ?1.00E-07?? ?1.00E-07?? ?9700878?? ?0?? ?1.00E-07?? ?63021.79?? ?12541354?? ?209.0226
?? ??? ??? ??? ??? ??? ??? ??? ??? ?
?? ??? ??? ??? ??? ??? ??? ??? ??? ?654.5287
?? ??? ??? ??? ??? ??? ??? ??? ??? ?
? ? ? ? ? ? ? ? ? ? ? ? ?
d0.1-4-10-4?? ??? ??? ??? ??? ??? ??? ??? ?
?? ??? ??? ??? ??? ??? ??? ??? ??? ?
f2[0]?? ?f2[1]?? ?f2[2]?? ?f2[3]?? ?迭代次數n?? ?平均準確率p-ave?? ?δ?? ?耗時ms/次?? ?耗時ms/199次?? ?耗時 min/199
0.536878?? ?0.460988?? ?0.46149?? ?0.460007?? ?4?? ?0?? ?0.5?? ?0.557789?? ?111?? ?0.00185
0.629137?? ?0.371521?? ?0.3726?? ?0.372414?? ?7?? ?0?? ?0.4?? ?0.155779?? ?31?? ?0.000517
0.7184?? ?0.281781?? ?0.280531?? ?0.280074?? ?12?? ?0?? ?0.3?? ?0.100503?? ?35?? ?0.000583
0.809433?? ?0.191093?? ?0.190154?? ?0.190257?? ?21?? ?0?? ?0.2?? ?0.236181?? ?47?? ?0.000783
0.902386?? ?0.097307?? ?0.097211?? ?0.097206?? ?43?? ?0?? ?0.1?? ?0.236181?? ?47?? ?0.000783
0.990031?? ?0.009969?? ?0.009966?? ?0.009967?? ?397?? ?0?? ?0.01?? ?2?? ?415?? ?0.006917
0.999?? ?1.00E-03?? ?1.00E-03?? ?1.00E-03?? ?3660?? ?0?? ?0.001?? ?15.26633?? ?3038?? ?0.050633
0.9999?? ?1.00E-04?? ?1.00E-04?? ?1.00E-04?? ?33662?? ?0?? ?1.00E-04?? ?115.1357?? ?22912?? ?0.381867
0.99991?? ?9.00E-05?? ?9.00E-05?? ?9.00E-05?? ?37338?? ?0?? ?9.00E-05?? ?126.6784?? ?25225?? ?0.420417
0.99992?? ?8.00E-05?? ?8.00E-05?? ?8.00E-05?? ?41802?? ?0?? ?8.00E-05?? ?144.9698?? ?28865?? ?0.481083
0.99993?? ?7.00E-05?? ?7.00E-05?? ?7.00E-05?? ?47443?? ?0?? ?7.00E-05?? ?166.5276?? ?33155?? ?0.552583
0.99994?? ?6.00E-05?? ?6.00E-05?? ?6.00E-05?? ?55259?? ?0?? ?6.00E-05?? ?190.598?? ?37929?? ?0.63215
0.99995?? ?5.00E-05?? ?5.00E-05?? ?5.00E-05?? ?65584?? ?0?? ?5.00E-05?? ?227.9196?? ?45361?? ?0.756017
0.99996?? ?4.00E-05?? ?4.00E-05?? ?4.00E-05?? ?81242?? ?0?? ?4.00E-05?? ?283.6382?? ?56453?? ?0.940883
0.99997?? ?3.00E-05?? ?3.00E-05?? ?3.00E-05?? ?107253?? ?0?? ?3.00E-05?? ?376.0503?? ?74842?? ?1.247367
0.99998?? ?2.00E-05?? ?2.00E-05?? ?2.00E-05?? ?158480?? ?0?? ?2.00E-05?? ?554.1608?? ?110278?? ?1.837967
0.99999?? ?1.00E-05?? ?1.00E-05?? ?1.00E-05?? ?308464?? ?0?? ?1.00E-05?? ?1076.221?? ?214177?? ?3.569617
0.999991?? ?9.00E-06?? ?9.00E-06?? ?9.00E-06?? ?341247?? ?0?? ?9.00E-06?? ?1192.693?? ?237353?? ?3.955883
0.999992?? ?8.00E-06?? ?8.00E-06?? ?8.00E-06?? ?382394?? ?0?? ?8.00E-06?? ?1328.07?? ?264294?? ?4.4049
0.999993?? ?7.00E-06?? ?7.00E-06?? ?7.00E-06?? ?435268?? ?0?? ?7.00E-06?? ?1515.171?? ?301527?? ?5.02545
0.999994?? ?6.00E-06?? ?6.00E-06?? ?6.00E-06?? ?504206?? ?0?? ?6.00E-06?? ?1757.176?? ?349694?? ?5.828233
0.999995?? ?5.00E-06?? ?5.00E-06?? ?5.00E-06?? ?600920?? ?0?? ?5.00E-06?? ?2055.226?? ?409007?? ?6.816783
0.999996?? ?4.00E-06?? ?4.00E-06?? ?4.00E-06?? ?744853?? ?0?? ?4.00E-06?? ?2519.915?? ?501466?? ?8.357767
0.999997?? ?3.00E-06?? ?3.00E-06?? ?3.00E-06?? ?980381?? ?0?? ?3.00E-06?? ?3350.477?? ?666746?? ?11.11243
0.999998?? ?2.00E-06?? ?2.00E-06?? ?2.00E-06?? ?1449669?? ?0?? ?2.00E-06?? ?4943.613?? ?983782?? ?16.39637
0.999999?? ?1.00E-06?? ?1.00E-06?? ?1.00E-06?? ?2818734?? ?0?? ?1.00E-06?? ?9529.804?? ?1896447?? ?31.60745
0.999999?? ?9.00E-07?? ?9.00E-07?? ?9.00E-07?? ?3123123?? ?0?? ?9.00E-07?? ?10445.02?? ?2078560?? ?34.64267
0.999999?? ?8.00E-07?? ?8.00E-07?? ?8.00E-07?? ?3493458?? ?0?? ?8.00E-07?? ?11695.43?? ?2327390?? ?38.78983
0.999999?? ?7.00E-07?? ?7.00E-07?? ?7.00E-07?? ?3972648?? ?0?? ?7.00E-07?? ?13545.04?? ?2695464?? ?44.9244
0.999999?? ?6.00E-07?? ?6.00E-07?? ?6.00E-07?? ?4605197?? ?0?? ?6.00E-07?? ?15193.38?? ?3023483?? ?50.39138
1?? ?5.00E-07?? ?5.00E-07?? ?5.00E-07?? ?5492530?? ?0?? ?5.00E-07?? ?18164.42?? ?3614719?? ?60.24532
1?? ?4.00E-07?? ?4.00E-07?? ?4.00E-07?? ?6800941?? ?0?? ?4.00E-07?? ?22708.23?? ?4518943?? ?75.31572
1?? ?3.00E-07?? ?3.00E-07?? ?3.00E-07?? ?8973350?? ?0?? ?3.00E-07?? ?30762.9?? ?6121852?? ?102.0309
1?? ?2.00E-07?? ?2.00E-07?? ?2.00E-07?? ?1.32E+07?? ?0?? ?2.00E-07?? ?44557.35?? ?8866912?? ?147.7819
1?? ?1.00E-07?? ?1.00E-07?? ?1.00E-07?? ?2.58E+07?? ?0?? ?1.00E-07?? ?88140.6?? ?17539982?? ?292.333
?? ??? ??? ??? ??? ??? ??? ??? ??? ?
??? ? ?? ? ?? ? ?? ? ?? ? ?? ? ?? ? ?? ? ?? ?950.8424

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